41-Issue 2

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/2633162

Browse

Browsing 41-Issue 2 by Subject "CCS Concepts: Applied computing --> Fine arts"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Vectorizing Line Drawings of Arbitrary Thickness via Boundary-based Topology Reconstruction
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Zhang, Zibo; Liu, Xueting; Li, Chengze; Wu, Huisi; Wen, Zhenkun; Chaine, Raphaƫlle; Kim, Min H.
    Vectorization is a commonly used technique for converting raster images to vector format and has long been a research focus in computer graphics and vision. While a number of attempts have been made to extract the topology of line drawings and further convert them to vector representations, the existing methods commonly focused on resolving junctions composed of thin lines. They usually fail for line drawings composed of thick lines, especially at junctions. In this paper, we propose an automatic line drawing vectorization method that can reconstruct the topology of line drawings of arbitrary thickness. Our key observation is that no matter the lines are thin or thick, the boundaries of the lines always provide reliable hints for reconstructing the topology. For example, the boundaries of two continuous line segments at a junction are usually smoothly connected. By analyzing the continuity of boundaries, we can better analyze the topology at junctions. In particular, we first extract the skeleton of the input line drawing via thinning. Then we analyze the reliability of the skeleton points based on boundaries. Reliable skeleton points are preserved while unreliable skeleton points are reconstructed based on boundaries again. Finally, the skeleton after reconstruction is vectorized as the output. We apply our method on line drawings of various contents and styles. Satisfying results are obtained. Our method significantly outperforms existing methods for line drawings composed of thick lines.